Welcome to the resource topic for 2022/1119
Title:
PESCA: A Privacy-Enhancing Smart-Contract Architecture
Authors: Wei Dai
Abstract:Public blockchains are state machines replicated via distributed consensus protocols. Information on blockchains is public by default—marking privacy as one of the key challenges.
We identify two shortcomings of existing approaches to building blockchains for general privacy-preserving applications, namely (1) the reliance on external trust assumptions and (2) the dependency on execution environments (on-chain, off-chain, zero-knowledge, etc.) with heterogeneous programming frameworks.
Towards solving these problems, we propose PESCA—a privacy-enhancing smart contract architecture. PESCA utilizes generic building blocks such as threshold fully-homomorphic encryption (FHE), distributed key generation (DKG), dynamic proactive secrete sharing (DPSS), Byzantine-fault-tolerant (BFT) consensus, and universal succinct non-interactive zero-knowledge proofs (zk-SNARKs).
First, we formalize the problem of replicating state machines augmented with threshold decryption protocols and discuss how existing BFT consensus protocols can be adapted to this setting. We describe how to instantiate a blockchain with a fixed FHE public key and have FHE-encrypted chain states programmatically decrypted via consensus.
Next, we describe a smart-contract framework for engineering privacy-preserving applications, where programs are expressed—in a unified manner—between four types of computation: transparent on-chain, confidential (FHE) on-chain, user off-chain, and zero-knowledge off-chain.
Lastly, to showcase the generality and expressiveness of PESCA, we provide two simple application designs for constant function market makers (CFMMs) and first-price sealed-bid auctions (FPSBAs), both with maximal privacy guarantees.
ePrint: https://eprint.iacr.org/2022/1119
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